Unless otherwise indicated herein, the approaches described in this section are not prior art to the claims in this application and are not admitted to be prior art by inclusion in this section.
A company typically queries data in the relational database to generate reports with the data. Thus, the relational database is designed to allow efficient retrieval of data. However, with the amount of data being stored in databases, a company may want to archive some of the data to create more space in the relational database. For example, the company archives the data stored in the relational database into an archive database. The archived data is typically stored in a compressed file in a proprietary format, and then the compressed file is stored in the archive database. This compressed file is unsearchable. Therefore, the archive database does not allow fast access and search capabilities with the archived data.
One solution to enable searching of the archived data requires that the company create an index for the archived data. To create the index, the company needs to determine which columns it wants to be able to do a look-up for before doing the indexing. For example, a company may want to index for the invoice number. In this case, the archived data may be indexed via the invoice number and a user can search for data via the invoice number. However, the searching is limited to the columns that were determined beforehand. A user cannot search for a term in a column that has not been indexed. A company may add more columns to improve the search through the archived data, but this also leads to additional database space consumption and complexity.